The effect of the Covid-19 shutdown on glycemic testing and control.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused a halt to in-person ambulatory care. We evaluated how the reduction in access to care affected HbA1c testing and patient HbA1c levels. METHODS: HbA1c data from 11 institutions were extracted to compare testing volume and the percentage of abnormal results between a pre-pandemic period (January-June 2019, period 1) and a portion of the COVID-19 pandemic period (Jan-June 2020, period 2). HbA1c results greater than 6.4% were categorized as abnormal. RESULTS: HbA1C testing volumes decreased in March, April and May by 23, 61 and 40% relative to the corresponding months in 2019. The percentage of abnormal results increased in April, May and June (25, 23, 9%). On average, we found that the frequency of abnormal results increased by 0.31% for every 1% decrease in testing volume (p < 0.0005). CONCLUSION: HbA1c testing volume for outpatients decreased by up to 70% during the early months of the pandemic. The decrease in testing was associated with an increase in abnormal HbA1c results.

Side-Effects of COVID-19 on Patient Care: An INR Story.

BACKGROUND: Numerous studies have documented reduced access to patient care due to the COVID-19 pandemic, including access to diagnostic or screening tests, prescription medications, and treatment for an ongoing condition. In the context of clinical management for venous thromboembolism, this could result in suboptimal therapy with warfarin. We aimed to determine the impact of the pandemic on utilization of International Normalized Ratio (INR) testing and the percentage of high and low results. METHODS: INR data from 11 institutions were extracted to compare testing volume and the percentage of INR results ≥3.5 and ≤1.5 between a pre-pandemic period (January-June 2019, period 1) and a portion of the COVID-19 pandemic period (January-June 2020, period 2). The analysis was performed for inpatient and outpatient cohorts. RESULTS: Testing volumes showed relatively little change in January and February, followed by a significant decrease in March, April, and May, and then returned to baseline in June. Outpatient testing showed a larger percentage decrease in testing volume compared to inpatient testing. At 10 of the 11 study sites, we observed an increase in the percentage of abnormal high INR results as test volumes decreased, primarily among outpatients. CONCLUSION: The COVID-19 pandemic impacted INR testing among outpatients which may be attributable to several factors. Increased supratherapeutic INR results during the pandemic period when there was reduced laboratory utilization and access to care is concerning because of the risk of adverse bleeding events in this group of patients. This could be mitigated in the future by offering drive-through testing and/or widespread implementation of home INR monitoring.

COVID-19 Pandemic Planning: Simulation Models to Predict Biochemistry Test Capacity for Patient Surges.

BACKGROUND: Patient surges beyond hospital capacity during the initial phase of the COVID-19 pandemic emphasized a need for clinical laboratories to prepare test processes to support future patient care. The objective of this study was to determine if current instrumentation in local hospital laboratories can accommodate the anticipated workload from COVID-19 infected patients in hospitals and a proposed field hospital in addition to testing for non-infected patients. METHODS: Simulation models predicted instrument throughput and turn-around-time for chemistry, ion-selective-electrode, and immunoassay tests using vendor-developed software with different workload scenarios. The expanded workload included tests from anticipated COVID patients in 2 local hospitals and a proposed field hospital with a COVID-specific test menu in addition to the pre-pandemic workload. RESULTS: Instrumentation throughput and turn-around time at each site was predicted. With additional COVID-patient beds in each hospital, the maximum throughput was approached with no impact on turnaround time. Addition of the field hospital workload led to significantly increased test turnaround times at each site. CONCLUSIONS: Simulation models depicted the analytic capacity and turn-around times for laboratory tests at each site and identified the laboratory best suited for field hospital laboratory support during the pandemic.